Forget Dick Fuld. Blame Carl Friedrich Gauss

Baruch has been forced out of (possibly temporarily) blogging hibernation by this piece, by one Sly Observer, who writes:

Nassim Taleb’s increasingly shrill followers have been yelling “black swan, black swan!” all year. This has irked me . . . I read Nassim Taleb’s book “The Black Swan” mainly to see what all the yelling was about and was unimpressed. The book can be summed up in the sentence “Options are under priced.” I found his open disdain for commerce very distasteful.

We can dismiss the “shrill” — a lazy, silly word, a cheap polemical trick unworthy of a response. But I take issue with the “yelling ‘black swan, black swan!'” It is certainly not what thoughtful followers of Taleb have been doing. In fact we have mostly stayed quiet, as far as I can see, deeply worried in general, and slightly embarrassed at the increasing visibility of what has become a catchphrase.

When Sly says he read Black Swan and thought the main message was “options are underpriced” I am reminded of pseudo-intellectual Otto (Kevin Kline) in A Fish Called Wanda, who says in response to Wanda’s accusation that he is an ape: “Apes don’t read philosophy!” Wanda says “Yes they do, Otto, they just don’t understand it.” “Options are underpriced” was actually a key message of Fooled by Randomness, Taleb’s first book. Black Swan is much more about the Gaussian fallacy, how financial strategies (not just financial) based on bell-curved distributions are not just incorrect but dangerous.

In case you have not read the book, or you did and didn’t understand it, the Gaussian fallacy is the idea that financial markets follow a standard, normal, mean-reverting, predictable distribution we can consistently exploit for fun and steady profit. Taleb would be the first to point out that some things do indeed follow Gaussian bell-curved distributions. Shoe sizes would be a good example. But in terms of trading markets the Gaussian ideal is very often a fallacy; big events, single days with big point moves in indices and stocks tend to be much more important in determining profit and loss over long periods, than the days when not much happens. Taleb’s key point is that very often, relying on a normal distribution holding true to make small but regular amounts of money is a big mistake; while we may only lose money rarely, when we do we can lose more than everything we made when things were good. He uses the metaphor of “picking up nickels in front of steamrollers.” It’s very apt.

We, and it seems capitalism itself, have just been flattened by the steamroller. We call our current mess the result of the housing bubble. But we could equally view it as the aftermath of a bubble in Gaussian strategies. The villains we point to on TV are the regulators, the hedge funds, the banks and, my favourite, the over-extended, ignorant home owners, but this is like blaming the water in the tidal wave for swamping the village. The set of ideas that justified their actions, the fake science, the epistemological error was what helped create the conditions for the wave itself. Amazingly, that this is the key error does not seem to be grasped yet, and as such is not going away. This, more than anything is what makes Baruch cross, and as such, focussing his Ire on a hapless blogger, of whom we should not expect too much (and who is a bit nicer about Taleb later in the post), may be unfair.I have thought long and hard about where we are and what has brought us here, and here are my conclusions; I give them to you to play with: Gaussian strategies may have self reinforcing tendencies. They dampen volatility themselves, temporarily, and make Gaussian thinking even more appealing in the short term. They spread into other, previously non Gaussian strategies. This will paradoxically tend to make the system more vulnerable to the sudden emergence of even a seemingly insignificant fat tail, and the consequences all the more devastating.

We saw, in the rise of Quant investing in the early part of this decade, the impact of billions of dollars of capital, leveraged 8-10x, being deployed to benefit from extreme moves in stocks, betting on mean reversion. It ironed those extreme moves out, reduced volatility and was, to start with, extremely profitable. That artifical calm created a stable base, a portfolio anchor and an epistemological model transmitted within the increasingly dominant multi-strat hedge funds to invade models in other strategies within those funds. Managers looked for steady, low volatility strategies which had huge capacity (were capable of running billions of dollars using the same strategy) and did not take directional market bets. Another very important transmission mechanism linking not just the hedge funds with each other but also hedge funds with other providers of financial products was the prime brokerage businesses of major banks. It was partly through this that banks started for example to package mortgages and flog them to the fixed income funds (also part of the multi strat), in the form of now-infamous CDOs.

The fund of fund guys loved it. They already used standard deviation of returns as a proxy for the riskiness of their investments in single and multi-strat funds. Now that all their investments started to use Gaussian language to express the basis for their own punting, the whole model became unified and much, much simpler. FoF was easy! Everything was easy. All you needed was to show that your “riskiness” was less than Joe’s down the road and you got money from the pension funds, other institutions and private bankers, the real investors in all this stuff, who themselves started presenting results to their trustees using VAR-based statistics in addition to their traditional Sharpe Ratios. The banks got their fees, the multi-strats got their 2 and 20, the FoFs got their 1 and 10 (or whatever), the punters got the 10% that was left and were jolly happy about it.

Volatility fell. Returns became more, not less reliable, if smaller, which was easily fixed by leverage, which was after all much safer nowadays, given the lower volatility, and wonderfully available, given an accomodative Fed. This expectation of easy, ever available liquidity went unsullied by any fears of inflation, given that Chinese and Indians were providing the same goods and services much cheaper than we would be doing ourselves, and were lending us the vast amounts of money we needed to buy ever more of the cheap and excellent stuff they were making for us. It was vendor finance on a galactic scale. Some more liquidity, sir? Said the prime brokers. Yes, please, said the hedgies, and get me a couple of spondoolicks of your best 2007 vintage subprime CDO. And so it continued.

This self-reinforcing “stability”, this wonderful confluence of events, was the basis the Great Moderation we lived through in the 6 years since 2001, and ended in August of 2007. I don’t want to make too much of the Gaussian contribution — it is somewhere in the structure, a contributing spar. At the base of the pyramid was steady house price appreciation and liquidity, driving extremely stable growth in consumer spending. I also don’t want to throw out some very good aspects of the Great Moderation. It brought us some very interesting technologies, but more than anything helped improve the lives of billions in China and India by bringing them into the global economy.

But the Gaussian is there nonetheless as an efficient if not sufficient cause of the Great Moderation going too far, reinforcing the totally fallacious sense of invulnerability and effortlessness that characterised the period. It is interesting that the first signs of the collapse occurred in the most Gaussian of sectors, the quant space, all the way back in August 2007. Ultimi Barbarorum had a rather good (even if I say so myself) explanation of this part of the crisis back then which was fairly widely read by the abnormal returns-reading econo-bloggy cognoscenti. I drew the same conclusions back then that I do now, and describe below.

What I think happened from there, my unprovable hypothesis, was that the demise of the quants (in part), and the start of house price depreciation (clearly most important), set off a number of ripples that destabilised the whole edifice. A cascade of unforeseen connected events followed, and a bunch of “hundred year storms” — really nothing of the kind, instead the phrase du jour of hedge fund managers writing to explain to investors why they lost large portions of their capital — progressively destroyed the “certainty” underlying other, ostensibly unconnected Gaussian and pseudo-Gaussian strategies. This showed the amazing extent to which these false certainties have pervaded our financial systems, in obscure and unexpected places.

A particularly obscure example are the KIKO hedges Korean corporates have used to hedge their dollar risk. Koreans are mega exporters to the US, and the seemingly inexorable drop in the USD was obviously hurting. So they hedged. Fair enough, but when you take on a KIKO (knock-in, knock-out) hedge you can actually get a preferential FX rate. You could make money. The downside was that once the KRW fell through a certain level you got “knocked out” — you had to pay double. Everyone “knew” the USD was going up, the idea of it going the other way was “inconceivable”. In 2007 and early 2008, according to Bloomberg, KIKO contracts many times the size of the amount of actual trade flows were taken out. Since the KRW tanked in the “flight to quality” dollar rally in the 2nd half of this year, chickens have come home to roost: a lot of these corporations may go bankrupt, facing huge FX losses. Additionally, it puts the Korean banking system at greater risk in addition to their exposure to the international credit freeze, increasing the potential for domestic defaults. I wonder what “a hundred year storm” is in Korean.

The leading participants in the financial system have been like the “cleverest man in the world” from the Princess Bride. The USD going up against the KRW? “Inconceivable!” House prices going down in the US for long enough to cause mass defaults? “Inconceivable!” Long held statistical relationships between linked securities going the other way? “Inconceivable!” Long standing investment banks going bust? “Inconceivable”! What, hedge funds lied about the “differentiated returns” bit, all use the same strategies and will see simultaneous, massive drawdowns? “Inconceivable!” You mean no-one’s on the other end? My credit default swap may be worthless? “Inconceivable”! I may not be able to issue commercial paper to fund my Q4 inventory build? “Inconceivable”! In each case, I am sure, those selling the strategies used evidence from a selection of past outcomes to show that the chances of the trades being unwound in a bad way were extremely unlikely, well outside the standard deviations of normal distributions. There was no redundancy built into the system. We thought we knew the odds, but the moment the system got stressed, we found out we had absolutely no idea what we were talking about.

Where do we go from here? What types of investment models will emerge from the ashes of our current markets? I think in many cases, it will be models with a lot of redundancy built in. We will keep money in lots of different banks. We will make sure we have a LOT of cash. We will make sure that not one, but multiple things will have to go wrong before we lose everything. We won’t use leverage. The models will also be simpler, and easier to understand.

In other cases, and this I find a more interesting idea, is that we will start to use strategies that embrace volatility, which benefit from the breaking of standard deviations, as opposed to the ones which make money within them. Current stat arb plays mean reversion. What if we were to start playing its opposite? A strategy for example that notes a historical relationship between stocks and tries to identify a point when it could break, and pockets the potentially major, unquantifiable profit when it does. Old style stock investing done properly is an example of this; I try and find stocks which can potentially move much, much farther than the analysts covering them think they can. That’s how stocks move in real life; they don’t go up or down in the neat 15-20% increments we find in analyst reports. If I can find one or two stocks that do 100% or 200% and I bet big, my year is made. The ones that don’t, well, I make sure I get out as quick as I can. It is a less sure, more variable existence, but it is honest. And a lot of things have to go wrong before I seriously blow up and wipe out my capital.

So that’s what I think. I have written about these things in the past, before all this happened. I won’t pretend I predicted it, I have lost too much money this year to do that convincingly. I am completely gobsmacked about how right Taleb has proved to be, however. How someone could read Black Swan after all this and be “unimpressed” is frankly beyond me.

I am impressed at such a scholarly reply to a blog I assumed would be read by exactly two people (maybe three if my wife got extremely bored).
Taleb said himself, as we have maintained for a year and a half, that this was extremely predictable and therefore didn’t qualify as a “Black Swan”.
The math to trade or run a successful business is the math of a shop keeper. Getting a quant in the door is a guarantee of eventual failure. Having a mathematician that doesn’t understand business managed by a business guy that doesn’t understand math is a situation with an inevitable failure waiting in the wings.
The events you refer to as “unforeseen” were in fact foreseen by many investors. Taleb specifically mentions the likely failure of Freddie and Fannie in his book.
Those of us on the right side of these trades have had to endure a year and a half of taunts as “doomers”.
Now we get “who could have seen it coming? I sat down with two people over a year ago for forty five minutes and explained the exact sequence of what later unfolded. Two weeks later I got a call that they had gone all in on bank stocks.
A black swan event is not a an event where a willful refusal to think causes your problems.

Well, Sly, as I said, I didn’t see this coming, so hats off to you that you did. I have also poked fun at “doomers” in good times, and let me apologise to you all for that. My position was that lots of doomers had predicted doom a few times too often, and in doing so had missed out on all the good stuff. Much better, I thought, to be long in good times and go short just after the bad stuff started. That’s where I have been most of the time, until yesterday, idiot that I am, when I announced to everyone at work it was time to own stocks for a couple of weeks. This afternoon I told them all it was time to get out again. There was less interest the second time around. Now, I give way to no-one in my pessimism!

Anyway, my point is not that the fact of a banking crisis was likely or unforeseen, these things do tend to happen, but all the weird stuff that has gone on as a consequence, the secondary effects of the original disturbance, like those weird KIKO contracts all blowing up. The ramifications are the things that are unforeseen. If I could have foreseen them, there’s no way I would be wasting my time blogging.

An imperfect metaphor is a break at pool. You can correctly foresee the fact that once someone hits the cue ball into the other balls they will all go everywhere, but I think you would have to be brave to forecast the positions the balls will end up in.

I agree with the metaphor to a large degree.
As the market is deceptively simple in that it only gives us two choices , up or down (abstaining could be argued as a third), I simply bet on the white hitting the pack.
Stretching the metaphor further I bet that the balls on the outside of the pack nearest the holes would be the most likely to sink if the pack was hit with enough force.
However the sequence of the collapse has been strikingly predictable to a fan of socioeconomics
and economic history.
History doesn’t repeat but it sure does rhyme.

I would like to correct the assumption that I am a “doomer”. Until May 2007 I was the ultimate blue sky’s and sunny days investor. The trick (far easier said than done) is to do what you said:
ride the good times wave then get short before others work out the party is over.
Not believing in your own innate genius is the best way to do this I’ve found. I trumpet my bad calls to everyone. It is so easy to get caught up in the “new paradigm” absurdity which is a never ending feature of human social interaction.

markets are social phenomenon not physical. A herd of sheep will approximate a gaussian dispersion, but then startle. Nobody ever models sheep dispersion or movement over time as a square of the mean distance, but pieces of paper pushed about by sheep, now that is a different story. Guassian or discrete models applied to social phenom represents a type 1 paradigm failure in my book. http://nickgogerty.typepad.com/designing_better_futures/2008/09/on-systemic-collapse.html